Enabling Drones Collaboration in ITS Applications Using a BDI Architecture Based on a 5-Dimensional Social Model

Abstract

Thanks to their capabilities to track objects and events of interest as well as their capabilities to provide unique real-time views of road sections, drones are being increasingly used in Intelligent Transportation System (ITS) applications. To deal with the highly complex ITS tasks, several approaches are allowing these drones to collaborate and ultimately achieve goals beyond their individual capabilities. Moreover, recent approaches are highlighting the need to empower drones with intelligence and autonomy, particularly to enable them react more efficiently to changes in the commonly open and highly dynamic ITS environments. Intelligence and autonomy will also enable drones optimize the use of their limited onboard resources. Within this perspective, we are proposing in this paper an intelligent drone collaboration approach using the Multi-Agent System paradigm. Based on a new generic Belief-Intension-Desire (BDI) architecture, our approach implements a five-dimension social model that mimics humans' reasoning and interactions. In contrast with the existing approaches, our solution enables drones to switch between selfish and collaborative behaviors. To demonstrate some benefits of our BDI architecture, we run simulations of two types of collaboration approaches; namely Collaboration based on Centralized Planning and Collaboration based on Participatory Planning. Our simulations are run to manage road traffic in the advent of an emergency situation like the COVID-19 pandemic.